Curtis Walker – UCAR/SUNY Oneonta Scott Sewell – NCAR/HAO

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Image Processing Algorithms for Aerosol Removal in Solar Coronal Images Curtis Walker – UCAR/SUNY Oneonta Scott Sewell – NCAR/HAO Steve Tomczyk – NCAR/HAO

Solar Corona Sun’s “Atmosphere” ~10⁶ K plasma Origin of the Solar Wind Emits massive quantities of energy Can only be seen naturally during total solar eclipse Total solar eclipse, July 11, 1991, observed at Hawaii. Photo Credit: S. Koutcmy, IAP-CNRS (France)

Solar Coronagraph LASCO Satellite Photo Credit: NASA SOHO Instrumentation that produces a false eclipse of the sun allowing coronal observation Ground-based and satellite-based varieties Zeiss Coronagraph at Lomnicky Peak Observatory in Slovakia Photo Credit: Steve Tomczyk

Image Processing Dark Frame Corrections Flat Field Corrections Aerosol Removal

What Do Aerosols Look Like?

Measurement of Aerosol Motion The white tracks represent aerosol trajectories over ~1s. Final image processed of 120 images.

How Do We Correct For Aerosols? Three techniques for image thresholds Mean Threshold Median Threshold Minimum Threshold A series of 120 images containing atmospheric aerosols were obtained in Boulder, CO on June 16, 2010 and were limited by the above thresholds.

Quality of Aerosol Removal Using Mean Threshold Mean threshold of all pixels in all 120 images. Note the aerosol streaks near the building and at left. Final image processed of 120 images.

Quality of Aerosol Removal Using Median Threshold Median threshold of all pixels in all 120 images. Note that this is the best result. Final image processed of 120 images.

Conclusions & Future Work We have successfully removed aerosols from an image utilizing the mean and median array thresholds We will still attempt the minimum array threshold and other techniques for comparison